THIS INVENTION relates to a multi-user code division multiple access receiver based on recursive estimation. More particularly the division relating to a method of receiving a code-division multiple-access signal.
Code division multiple access (or CDMA) cellular communications systems suffer from co-channel interference (or multi-user or multiple-access interference [MAI]) on the reverse or up link (i.e. from a mobile handset to a base station). This is due to the impossibility of maintaining orthogonality between code channels used by independent mobile handsets, which transmit asynchronously. This form of interference limits the uplink capacity severely, and very significant capacity gains can be achieved if multi-user interference can be reduced, or if joint detection of all users is employed, as opposed to conventional single-user detection techniques currently in use which merely treat multiple-access interference (MAI) as uncorrelated noise.
Previous work on MAI cancellation dates back to S. Verdu, "Minimum probability of error for asynchronous Gaussian multiple-access channels," IEEE Trans. Inf. Theory, vol. 32, no. 1, pp. 85-96, January 1986, which describes the use of a Viterbi decoder in concert with a maximum-likelihood (ML) decoding metric for the demodulation of the bits transmitted by each user. The maximum-likelihood detector has a complexity which increases exponentially--in a binary phase shift keyed (BPSK) system, this is of the order of 2.sup.k multiply-and-add's, K being the number of users in the system. Its complexity prevents the practical implementation of the ML detector, and thus other sub-optimal schemes have been proposed.
Among these, direct descendants of Verdu's ML detector are the sequential decoder discussed in Z. Xie, C. K. Rushforth, and R. T. Short, "Multi-user signal detection using sequential decoding," IEEE Trans. Communications, vol. 38, no. 5, pp. 578-583, May 1990, and a limited tree-search detector discussed in L. Wei, L. K. Rasmussen, and R. Wyrwas, "Near-optimum tree-search detection schemes for bit-synchronous multi-user CDMA systems over Gaussian and two-path Rayleigh fading channels," IEEE Trans. Communications, Vol. 45, No. 6, pp. 691-700, June 1997, which operate on the principle of searching the decoding tree structure non-exhaustively, as opposed to the ML algorithm which examines every branch of the tree. The complexity of such schemes is still fairly large, and their structure is more suited to a programmable digital signal processor (DSP) implementation than a large-scale integrated (LSI) circuit one. Present DSP's are still not powerful enough to implement the tree-search family of multi-user detectors.
The conventional detector passes the received signal through a filter bank, each branch of which is matched to the spreading code of one user. The K outputs of the filter bank are then passed through K decision devices (or slicers) which decide on the symbols that were transmitted. This simple technique suffers from MAI as described earlier, but an additional matrix filter based on the cross-correlations between the spreading codes used by individual users can be designed to remove MAI completely. This detector structure is known as the decorrelating detector and was proposed in R. Lupas and S. Verdu, "Linear multi-user detectors for synchronous code-division multiple-access channels," IEEE Trans. Inf. Theory, vol. 35, no. 1, pp. 123-136, January 1989.
The problems with the decorrelating detector are that:
1. when long spreading codes with periods greater than the symbol interval are used, the matrix filter has to be re-calculated in every symbol. This is a non-trivial operation requiring the inversion of a K.times.K matrix; PA1 2. with long codes, there is a non-zero probability that in a given symbol interval, the codes selected by the K users will not form a linearly independent set. This would be fatal to the decorrelating detector; and PA1 (a) converting the CDMA signal to a baseband signal; PA1 (b) recognising symbol boundaries in every multipath for every user in the baseband signal to produce a delay estimate; PA1 (c) estimating an attenuation and phase rotation impressed on the signal by each multipath to produce channel estimates; PA1 (d) generating new symbol estimates for every user at a sampling rate that is greater than a symbol rate of the signal; PA1 (e) generating an estimate of the received signal using said that is greater than a symbol rate of the signal symbol estimates and channel estimates; PA1 (f) comparing the received signal with its estimate and feeding estimation error back to a means for estimating the transmitted symbols; PA1 (g) sampling the symbol estimates at the estimated symbol boundaries of each user to obtain final symbol estimates; and PA1 (h) repeating steps (b) through (g) with every new sample.
3. The decorrelating detector removes MAI without regard for noise and interference from other sources, and can be shown always to increase the noise component not due to MAI. This noise enhancement problem is a characteristic of zero-forcing filters such as the decorrelating detector.
The first two problems are almost impossible to overcome due to the very concept of the decorrelating detector, which is to invert the channel matrix in order to recover the transmitted signal vector.
The noise enhancement problem can be limited using the same technique as in channel equalisation, namely the use of a minimum mean squared error (MMSE) solution. This was proposed in Z. Xie, R. T. Short, and C. K. Rushforth, "A family of sub-optimum detectors for coherent multi-user communications," IEEE J. Sel. Areas Comms., vol. 8, no. 4, pp. 683-690, May 1990, and further explored in U. Madhow and M. L. Honig, "MMSE interference suppression for direct-sequence spread-spectrum CDMA," IEEE Trans. Communications, vol. 42, no. 12, pp. 3178-3188, December 1994. The MMSE detector also in theory requires a matrix inversion, and in addition to knowledge of spreading codes, also requires knowledge of the thermal noise power at the receiver. This may seem impractical, but the amount of side information required can be reduced to merely a training sequence when an adaptive implementation is applied. This approach is expounded in, for example, S. L. Miller, "An adaptive direct-sequence code-division multiple-access receiver for multi-user interference rejection," IEEE Trans. Communications, vol 43, no. 2/3/4, pp. 1746-1755, February/March/April 1995, S. Verdu, "Adaptive multi-user detection," in Code Division Multiple Access Communications, S. G. Glisic and P. A. Leppanen, Eds., pp. 97-116, Kluwer Academic Publishers, The Netherlands, 1995, and a blind approach not requiring the use of training symbols has also been proposed in M. Honig, U. Madhow, and S. Verdu, "Blind adaptive multi-user detection," IEEE Trans. Inf. Theory, vol. 41, no. 4, pp. 944-960, July 1995.
The adaptive MMSE detector however suffers from one major drawback in that it can only be used for short-code systems, i.e., those which use spreading codes with periods exactly equal to one symbol interval. Such systems do not currently exist and are not under consideration for future cellular systems because of the need to have codes long enough to uniquely identify every single mobile handset in use at one time around the world.
Another family of multi-user detectors works on the principle of interference cancellation through progressive subtraction of estimated interference components from the received signal. The successive interference canceller (SIC) as discussed in P. Patel and J. Holtzmann, "Analysis of simple successive interference cancellation scheme in a DS/CDMA system," IEEE J. Sel. Areas Comms., vol. 12, no. 5, pp. 796-807, June 1994, and the parallel interference canceller (PIC) discussed in M. K. Varanasi and B. Aazhang, "Multi-stage detection in asynchronous code-division multiple-access communications," IEEE Trans. Communications, vol. 38, no. 4, pp. 509-519, April 1990, are well known and many improvements have been made to the basic structures. Notable ones include hybrid serial-parallel structures as discussed in M. Sawahashi, H. Andoh and K. Higuchi, "DS-CDMA pilot and data symbol-assisted coherent multistage interference canceller using repeatedly updated channel estimation," in the Proc. IEEE Int'l Conf. Comm. Systems (ICCS)/Int'l Wkshop Intelligent Sig. Proc. & Comm. Systems (ISPACS), Singapore, November 1996, pp. 585-589 and the use of tentative decisions at the output of each stage instead of hard decisions as discussed in U.S. Pat. No. 5,579,304 and D. Divsalar and M. Simon, "Improved CDMA performance using parallel interference cancellation," Tech. Rep. 95-21, Jet Propulsion Lab., California Inst. of Tech., October 1995. The linear clipper soft-decision function in particular produces quite spectacular improvements in performance over the hard-decision SIC, as shown in X Zhang and D. Brady, "Soft-decision multistage detection for asynchronous AWGN channels", in the Proc. 31st Annual Allerton Conf. Comms., Cont. & Comp., Monticello, Ill., 1993 and for another algorithm in L. B. Nelson and H. V. Poor, "Iterative multi-user receivers for CDMA channels: an EM-based approach," IEEE Trans. Communications, vol.44, No. 12, pp.1700-1710, December 1996.
Various forms of the subtractive interference canceller are disclosed in U.S. Pat. No. 5,579,304; 5,218,619; 5,467,368; and 5,363,403.
Due to the large number of different types of multi-user CDMA detectors which have been proposed, it is quite a task to rank them according to performance beyond noting that the ML detector performs best while the conventional detector performs worse. Therefore, we do not claim that this invention performs better than all other multi-user CDMA detectors, only that against a similar detector described in D. S. Chen and S. Roy, "An adaptive multi-user receiver for CDMA systems" IEEE J. Sel. Areas Comms., vol. 12, no 5, pp. 808-816, June 1994, it does perform a lot better and against a four-stage linear-clipper SIC, performance is comparable as will be demonstrated later.
In D. S. Chen and S. Roy, "An adaptive multi-user receiver for CDMA systems" IEEE J. Sel. Areas Comms., vol. 12, no 5, pp. 808-816, June 1994, a detector which operates on the basis of recursive least squares (RLS) weight updating and the concept of regenerating the received signal based on known spreading codes and channel coefficients was described. The channel model used is similar to the one described herein, but it assumes synchronous transmission, i.e., all users' symbol intervals are synchronized, whereas this invention explicitly includes asynchronous systems. Also, the weight up-dating algorithm described herein differs from the RLS algorithm used in D. S. Chen and S. Roy, "An adaptive multi-user receiver for CDMA systems" IEEE J. Sel. Areas Comms., vol. 12, no 5, pp. 808-816, June 1994.
In T. J. Lim and L. K. Rasmussen, "Adaptive symbol and parameter estimation in asynchronous multi-user CDMA detectors", IEEE Trans. Communications, vol. 45, no. 2, pp. 213-220, February 1997, a joint parameter estimation and bit detection algorithm using the extended Kalman filter (EKF) was proposed. The novelty in that algorithm lay in the joint adaptation of time delay estimates and bit estimates with the EKF, which differs from the Kalman filter used in this invention because the latter can be used only when time delays are assumed to be known.